[Note: All reference numerals begin with the Figure number; i.e. numeral 1022 refers to FIG. 10, numeral 701 refers to FIG. 7]
In many electronic imaging applications, such as ultrasound and radar, information about the objects being imaged is acquired in a non-Cartesian coordinate system. FIG. 1A shows a radar or ultrasound system 100, which sends out radial scans 104, 106, in order to build an image of an object 102. The resulting echoes form the raw data (FIG. 1B), which are usually in polar coordinates, relative to an origin 107. Referring to FIG. 1C, an image 110 of the object 102 must be displayed on a display terminal 108, such as a CRT or LCD monitor. In order for the object 102 to be displayed on the display device 108, the data must be converted into the coordinate system of the display device 108, which is often different from the coordinate system of the raw data (FIG. 1B).
A ‘scan converter’ is the name given to a system which converts raw data from one coordinate system into another.
Scan conversion systems face three challenges: Speed, accuracy, and cost.
In the most common case, the imaging system must run in real-time, and display an image thirty or more times per second. One scan conversion must be performed for each image, so thirty or more scan conversions must be performed each second. The speed of a scan conversion system is defined by the number of images which it can scan convert per second, or, equivalently, the time it takes to scan convert a single image.
Because the raw image data (FIG. 1B) is acquired in a different coordinate system, and very often with a different resolution than the display monitor 108, there is not a simple one-to-one mapping between the raw data points (FIG. 1B) and the points on the display 108. In some areas of the display image, multiple raw data points may map to a single display point; in other areas of the display image, no raw data point will directly map to a display point, leaving ‘holes’ in the image. These two phenomena can lead to ‘artifacts’, speckle or blemishes in the resulting image. Further, certain scan converters use various approximations in an attempt to minimize processing and speed up scan conversion. These approximations can further degrade the resultant image. There is usually a trade-off between speed and accuracy.
The most advanced systems achieve real-time speed and also excellent accuracy, at the expense of cost. Such systems are usually unacceptably expensive, due to the enormous computing power they require. Further, existing systems are often inflexible, because either they require custom hardware, or they use a dedicated general purpose CPU or a dedicated DSP processor. If a more efficient method of scan conversion existed, not only would the cost of the required hardware be reduced, but the flexibility of the systems would be increased, because the scan conversion algorithm would use only a fraction of the available computing resources.
As is shown infra, existing systems do not make efficient use of their computing resources. There is a need for a scan conversion algorithm which makes more efficient use of computing resources, thus lowering the cost of the system, and increasing flexibility.